Causality has been the objective of econometrics for many years. I always wonder why people in machine learning overlook it's contributions. They almost never discuss it (even to criticize it) and prefer reinventing the wheel.
In Academia and in "more reputable" projects, domain knowledge is vital to the success of an ML project. This doesn't seem to be the case for startups, looking to make some quick cash. Lots of online articles tout the lack of domain knowledge needed to create models... just googling "machine learning without domain knowledge" brings up a ton of articles saying machine learning is "easy" even without expert knowledge.